# @Time : 2020/9/23
# @Author : Yushuo Chen
# @Email : chenyushuo@ruc.edu.cn
# UPDATE
# @Time : 2020/9/23, 2020/12/28
# @Author : Yushuo Chen, Xingyu Pan
# @email : chenyushuo@ruc.edu.cn, panxy@ruc.edu.cn
"""
recbole.data.dataloader.user_dataloader
################################################
"""
import torch
from recbole.data.dataloader import AbstractDataLoader
from recbole.data.interaction import Interaction
from recbole.utils.enum_type import DataLoaderType, InputType
[docs]class UserDataLoader(AbstractDataLoader):
""":class:`UserDataLoader` will return a batch of data which only contains user-id when it is iterated.
Args:
config (Config): The config of dataloader.
dataset (Dataset): The dataset of dataloader.
batch_size (int, optional): The batch_size of dataloader. Defaults to ``1``.
dl_format (InputType, optional): The input type of dataloader. Defaults to
:obj:`~recbole.utils.enum_type.InputType.POINTWISE`.
shuffle (bool, optional): Whether the dataloader will be shuffle after a round. Defaults to ``False``.
Attributes:
shuffle (bool): Whether the dataloader will be shuffle after a round.
However, in :class:`UserDataLoader`, it's guaranteed to be ``True``.
"""
dl_type = DataLoaderType.ORIGIN
def __init__(self, config, dataset, batch_size=1, dl_format=InputType.POINTWISE, shuffle=False):
self.uid_field = dataset.uid_field
self.user_list = Interaction({self.uid_field: torch.arange(dataset.user_num)})
super().__init__(config=config, dataset=dataset, batch_size=batch_size, dl_format=dl_format, shuffle=shuffle)
[docs] def setup(self):
"""Make sure that the :attr:`shuffle` is True. If :attr:`shuffle` is False, it will be changed to True
and give a warning to user.
"""
if self.shuffle is False:
self.shuffle = True
self.logger.warning('UserDataLoader must shuffle the data')
@property
def pr_end(self):
return len(self.user_list)
def _shuffle(self):
self.user_list.shuffle()
def _next_batch_data(self):
cur_data = self.user_list[self.pr:self.pr + self.step]
self.pr += self.step
return cur_data